The objectives ofthe Data Management and Modeling Core (DMMC) are to provide integrated biostatistics, bioinformatics, and database management support for all Projects ofthe U-M NIEHS/EPA Children's Environmental Health and Disease Prevention Center (CEHC). The DMMC will promote integration of knowledge and understanding of common statistical, bioinformatics, and database issues across the U-M CEHC, and accelerate the research goals ofthe projects by not only fully engaging in all aspects ofthe U-M CEHC, but also employing appropriate and advanced study design and data analysis methodologies that can enhance the types of research questions addressed by study data. The primary aims ofthe core include (i) providing statistical and bioinformatics support for all projects, including study design, conduct of statistical analyses, integration with biological information and interpretation of research findings, (ii) supporting data management, data quality controls, and integration of databases for conduct of the projects, and (iii) participating in dissemination of research findings, including writing of manuscripts and presentations, and data sharing and dissemination strategies. The DMMC personnel have a great wealth of knowledge and experience of analyzing longitudinal data and genetic/genomic data, including mixed-effects models, GEE models, joint modeling of longitudinal and survival data, robust mixed-effects models, modern variable selection techniques (e.g. group-lasso), novel methods of handling missing data and high-throughput data analysis and biomarker network analysis for interpretation of metabolomic data. All these are critical and beneficial to the study aims in all projects. To study mixtures of exposures, an innovative approach based on the multi-index regression model will be applied to identify important pollutants and pollutant mixtures that may be associated with somatic grov\/th, sexual maturation, and metabolomic outcomes.